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Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics

Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics

(12 customer reviews)

Original price was: $59.99.Current price is: $19.98.

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Master the math needed to excel in data science and machine learning. If you’re a data scientist who lacks a math or scientific background or a developer who wants to add data domains to your skillset, this is your book. Author Hadrien Jean provides you with a foundation in math for data science, machine learning, and deep learning. Through the course of this book, you’ll learn how to use mathematical notation to understand new developments in the field, communicate with your peers, and solve problems in mathematical form. You’ll also understand what’s under the hood of the algorithms you’re using. Learn how to: Use Python and Jupyter notebooks to plot data, represent equations, and visualize space transformations Read and write math notation to communicate ideas in data science and machine learning Perform descriptive statistics and preliminary observation on a dataset Manipulate vectors, matrices, and tensors to use machine learning and deep learning libraries such as TensorFlow or Keras Explore reasons behind a broken model and be prepared to tune and fix it Choose the right tool or algorithm for the right data problem

12 reviews for Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics

  1. Court Miller (verified owner) –

    My team references this book often when explaining why they formed a conclusion from data. It’s core to our business and this book outlines so comprehensively the methods of doing it right, identifying bias, and ensuring our conclusions are accurate.

    This is not a how-to book. It’s not even a book on math, really. This is the “why” behind working with data. It is the definitive handbook on data that every data scientist, analyst, business manager should understand before working with data.

    If you work with data – and just as importantly – if you rely on a team that works with data, this needs to be on your bookshelf.

  2. CookieWizard (verified owner) –

    I came to this with very little stats and linear algebra knowledge and no calculus. The author goes into just enough detail to be able to understand the math without getting overwhelmed, and the Python implementations really help break up the content and stick the math into your mind. The chapters build on each other with a final chapter on Neural Networks integrating everything you have learned previously. This chapter was a bit hard for me to completely follow and I plan to revisit it after some additional math training. This is a book I think I will go back to again and again through the next couple of years.

  3. Issa Ayoub (verified owner) –

    All of the material presented in this book are important/excellent. My only comment is with regard to the grammatical mistakes which confuses the reader sometime. All in all, I highly recommend the book.

  4. Marcelo Rezende Módolo (verified owner) –

    A leitura é fácil e os exemplos podem ser testados com facilidade.

  5. Cooking Texan (verified owner) –

    Since I retired over 20 years ago, I lost much of my familiarity with mathematical and statistical concepts. This book provides a good review of those concepts and made me happy to visit them again.

  6. Amazon Customer (verified owner) –

    I really enjoy the break down of the concepts and how they are applied in Data Science.

  7. Chaminda Ranasinghe (verified owner) –

    This book gives a simple and methodical background to the use of math in DS. The author makes sure that there are no gaps in the introduction of math knowledge of the reader when explaining the algorithms. This book makes you appreciate the theories behind DS and ML.

    The final chapter discloses the reality in the demand vs hype of DS skills, which is honest and valuable.

    Few errors in the narrations which should be fixed in the next revision.

  8. Hemal (verified owner) –

    This is one of the best books I have read, really explaining the fundamentals of math like never explained before. I am also making by teenagers read this book to clarify some concepts and develop more interest in mathematics. I highly recommend this book.

  9. tb (verified owner) –

    All math equations are broken in Kindle edition. Unable to read them on kindle scribe. Returned the book. But please fix it.

  10. mnowa (verified owner) –

    Presents mathematical concepts in an approachable way that is actually applicable to DS. When they told you the math would be useful some day, this book actually points out why in terms of DS problems.

  11. Don (verified owner) –

    Comprehensive material. Using it to get smart on the latest data science work.

  12. nesha.st (verified owner) –

    Interests

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